Netskope Skylight

Agent Action Control

Say yes to agentic AI, because a security policy decides what agents can do before they act, not after.

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Control what your AI agents can do

91% of organizations cannot stop a risky agent action before it executes. Netskope Skylight Agent Action Control classifies each agent action by risk, from data destruction to credential misuse, and blocks, allows, or alerts on it before it executes, so security decides what happens next.

Deploy agents with confidence
features and benefits

Keep a human in the loop and prevent destructive agent behavior.

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Agent action classification

Classify every AI agent action into one of nine categories, from data destruction to credential manipulation, and assign each a risk level based on what it touches and in what way, so no action goes unaccounted for.

Enforce risk-based policies

Build a policy that decides whether an action gets blocked, allowed, or flagged for an alert, with different profiles for a coding assistant than a chat application, so policy fits the agent, not the other way around.

Extend existing enforcement points

Enforce every decision on network traffic, with enforcement points across the Netskope platform, so there’s no new console or blind spot to manage.

Netskope Skylight Agent Action Control use cases

AI agent visibility

Detect every AI agent acting across API and MCP, and see exactly what it's doing to close the blind spot most security teams have today.

Risk-based agent policies

Assign a risk level to each category of agent action, from source code changes to infrastructure provisioning, so security can decide what to block, allow, or sound the alert on: before it happens.

Automated action blocking

Stop a critical-risk action, such as deleting a production repository, before the call ever reaches its target, instead of writing an incident report after the damage is done.

Credential and secret protection

Stop AI agents from manipulating credentials and secrets outside of their intended scope, closing off one of the most common paths from an agent action to a breach.

Safe agentic coding adoption

Allow engineering teams to use coding agents such as Cursor, Claude Code, and ChatGPT by governing what those agents can touch, rather than blocking adoption outright.

AI in The Fast Lane Roadshow

Dans une ville proche de chez vous.

Le roadshow AI in the Fast Lane de Netskope réunit des professionnels de la sécurité pour discuter de la façon dont les organisations utilisent l'IA aujourd'hui et de la manière dont une stratégie de sécurité globale peut créer un modèle plus intelligent, plus sûr et à l'épreuve du temps. Cet événement essentiel et interactif s'adresse aux praticiens et aux cadres des réseaux et de la sécurité qui cherchent à exploiter la puissance de l'IA tout en maintenant la sécurité et la conformité.

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FAQ

What is Netskope Skylight Agent Action Control? How does it work with the infrastructure we already have? What kinds of agent actions does it classify?

What is Netskope Skylight Agent Action Control?

Netskope Skylight Agent Action Control classifies every action an AI agent attempts into one of nine risk categories, such as data destruction or credential manipulation, then lets security teams block, allow, or alert on it before it executes, not after.

How does it work with the infrastructure we already have?

It runs on network traffic Netskope already inspects. Netskope One Next Gen SWG (NG-SWG) enforces the decision for API traffic, and Netskope Skylight Agentic Broker enforces it for MCP traffic, so there’s no new console to manage.

What kinds of agent actions does it classify?

Nine categories, including access control changes, credential and secret manipulation, data destruction, infrastructure provisioning, potential data exfiltration, potential external communication, remote code execution, and source code changes.